Competitive learning neural networks applied to multivariate data set reduction

Presents three competitive learning neural networks applied to the multivariate data set reduction problem. The synaptic vectors of a neural network are used as prototypes of the data set. The quality of the results are compared, using an example, by means of an informational criterion. This criterion evaluates the quality of the matching between the density function estimated from the whole data set and that determined from the reduced set